Jun Ohya
Papers
9
Total Citations
35
H-Index
4
About
Jun Ohya is a leading researcher in computer vision and robotics, with key contributions spanning human-robot interaction, medical image analysis, and disaster response automation. His work on hand-gesture recognition from moving cameras—using the innovative Human-Following Local Coordinate system—has advanced human-to-robot interfaces, enabling mobile robots to interpret gestures in dynamic environments. In medical imaging, Ohya developed an automatic method for detecting fetal position in ultrasound images using CNN fine-tuning and Grad-CAM, achieving 7 citations for its potential to improve prenatal diagnostics. His most impactful work, however, lies in disaster response robotics: he has pioneered autonomous systems for manipulating valves, drills, and switches in hazardous sites, with papers on valve detection (6 citations) and stair navigation (6 citations) demonstrating robust performance using RGB-D sensors and 3D point cloud analysis. Ohya’s research also extends to assistive robotics, including a chewing detection method for care robots using variable-intensity templates. With over 30 citations across his top papers, his work is shaping safer, more capable robots for real-world challenges—from disaster zones to healthcare settings.
Research Focus
Key Achievements
Top Papers
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- 2Study on human gesture recognition from moving camera images6 citations · 2010
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